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Previous information systems studies focused on studying people’s receptivity towards innovation acceptance using variables borrowed from the psychology theories that focus on behavioral determinants. There is a lack of researches, which used the informational determinants that may induce receptivity of individuals to accept innovations introduced by inventors. This paper develops a logical model of innovation process based on modeling the principles of user informational-based readiness factors, which are Exposure, Awareness, Experience, and Knowledge. It is a step to establish an approach for understanding the adoption and diffusion process of innovations by individuals. This approach must be apart from using the behavioral, psychological, which is currently led by most information systems theories. The researcher in this study synthesized the existing literature review of the proposed informational instrument, which forms the Users Information-Based Readiness (UIBR). The researcher used a modeling technique called Unified Modeling Language (UML) tools, mainly the use case and Data Flow Diagram (DFD). The logical process model for innovation diffusion created to represent the input data flow and output data flow to each process in the innovation diffusion. The paper’s main findings include the development of a model of user informational preparedness for innovation acceptance. The model offers a method for people to know and locate the status of innovations in adoption. The researcher built this model based on the informational readiness concepts using four chains of commands that move adopters from process to another and from stage to another stage in a hierarchical chain. These four phases categorized into four sequential processes, namely Exposure, Awareness, Experience, and Knowledge. Researchers expect the developed model to provide the right direction for understanding the technology adoption process. It also helps the innovator, inventor, government, industry, and decision-makers to leverage their resources and time to design the strategy for innovation diffusion and implementation successfully.

Dynamics Process of Innovation Diffusion Model: Actor-Network Theory Approach